Automated Detection of Apical Foreshortening in Echocardiography Using Statistical Shape Modelling

Automated detection of foreshortening, a common challenge in routine 2-D echocardiography, has the potential to improve quality of acquisitions and reduce the variability of left ventricular measurements. Acquiring and labelling the required training data is challenging due to the time-intensive and highly subjective nature of foreshortened apical views. We aimed to develop an automatic pipeline for the detection of foreshortening. To this end, we propose a method to generate synthetic apical-four-chamber (A4C) views with matching ground truth foreshortening labels.
Source: Ultrasound in Medicine and Biology - Category: Radiology Authors: Tags: Original Contribution Source Type: research